Functional Brain Network of Trait Impulsivity: Whole-Brain Functional Connectivity Predicts Self-Reported Impulsivity.

Given impulsivity's multidimensional nature and its implications across various aspects of human behavior, a comprehensive understanding of functional brain circuits associated with this trait is warranted. In the current study, we utilized whole-brain resting-state functional connectivity data of healthy males (n = 156) to identify a network of connections predictive of an individual's impulsivity, as assessed by the Barratt Impulsiveness Scale (BIS)-11. Our participants were selected, in part, based on their self-reported BIS-11 impulsivity scores. Specifically, individuals who reported high or low trait impulsivity scores during screening were selected first, followed by those with intermediate impulsivity levels. This enabled us to include participants with rare, extreme scores and to cover the entire BIS-11 impulsivity spectrum. We employed repeated K-fold cross-validation for feature-selection and used stratified 10-fold cross-validation to train and test our models. Our findings revealed a widespread neural network associated with trait impulsivity and a notable correlation between predicted and observed scores. Feature importance and node degree were assessed to highlight specific nodes and edges within the impulsivity network, revealing previously overlooked key brain regions, such as the cerebellum, brainstem, and temporal lobe, while supporting previous findings on the basal ganglia-thalamo-prefrontal network and the prefrontal-motor strip network in relation to impulsiveness. This deepened understanding establishes a foundation for identifying alterations in functional brain networks associated with dysfunctional impulsivity.

Nature-based solutions for improving food security: A systematic global review.

Nature-based solutions (NBS) have been promoted as a holistic way to solve a variety of societal issues while benefiting biodiversity at the same time. To date, applications of NBS approaches that help ensure food security have yet been systematically reviewed. In this paper, we critically review the specific NBS for food security, highlighting their limitations, to provide recommendations that promote their applications for improving global food security. We accessed and evaluated publications on four different scholastic databases, and our systematic review of relevant materials indicated that many NBS approaches can be applied to enhance food security dimensions individually or together. However, there is a strong bias towards food availability, and not enough research has been done to link NBS with improvements in food access and utilization. Over 80 % of the reviewed papers were of short-term studies or without specific timeframes, and 25 % offered no information on the economic effectiveness of NBS. Environmental benefits of NBS were explicitly described in about 60 % of these papers, and biodiversity enhancement was measured in only about 10 %. We, therefore, recommend future applications of NBS to safeguard food security be shifted to food access and utilization with careful consultation with local communities to address their specific context, using indicators that are easily measured and managed. Systematic monitoring regimes and robust and diversified financial support systems are also equally important in efforts to successfully implement NBS. Moreover, environmental and societal benefits, especially water productivity and biodiversity, must be incorporated into the planning and design of NBS.

HCMV detection in Asian gastric cancer RNA-seq data sets and clinical validation in Indian GC patients reveals the HCMV-GC specific gene signatures.

Gastric cancer (GC) prevalence is very high in the Asian population. Oncogenic viruses play a crucial role in the progression of different types of cancers. Through reanalysis of clinical RNA-seq data sets derived from Asian GC patients, this study identified the presence of human cytomegalovirus (HCMV) in Asian GC tumors, next to the well-studied association of EBV. Clinical recruitment of the Indian GC cohort and screening for HCMV presence identified a 14.28% occurrence, similar to that observed in the bioinformatics analysis. A combinatorial approach of rank-based meta-analysis and ranking of groups based on an expectation-maximization algorithm identified that the upregulated LINC02864 and MAGEA10 correlated with poor survival of GC patients and downregulated tumor suppressor genes enriching for gastric acid secretion pathway to be associated with HCMV-positive GC patients, revealing the progressive role of HCMV infection in GC. Genes that discriminate between different stages of GC were identified through feature selection implemented in a machine-learning approach. LTF and KLK10 expressions were found to be specifically dysregulated by HCMV and can also indicate the GC stages. The results of this study will guide future studies to identify the functional role of these genes in the HCMV-associated GC.IMPORTANCENearly 75% of gastric cancer (GC) cases reported globally are from the Asian population. Most existing public databases, such as TCGA, comprise only a fractional portion of data derived from Asian ancestry. This study identified EBV and human cytomegalovirus (HCMV)'s higher detection in GC patients. The presence and role of EBV associated with GC are well-known, and the observation of HCMV prompted us to validate the findings in a small cohort of 40 Indian GC patients. We observed a 14.28% occurrence of HCMV in the Indian cohort, similar to that observed from next-generation sequencing. A combinatorial approach of rank-based meta-analysis and ranking of groups based on an expectation-maximization algorithm identified that the upregulated LINC02864 and MAGEA10 correlated with poor survival of GC patients and downregulated tumor suppressor genes enriching for gastric acid secretion pathway to be associated with HCMV-positive GC patients, revealing the progressive role of HCMV infection in GC.

Assessment of Valance Emotional State Using EEG-EDA Coupling and Explainable Classifiers.

Emotion influences human life and impacts daily life activities. During emotional processes, physiological signals interact with each other instead of functioning separately. Although unimodal and multimodal approaches have been explored for emotion classification, there is a lack of inclusion of central and peripheral nervous system signal interaction-based approaches. In this study, an attempt has been made to characterize valance emotional states using Electroencephalogram (EEG)- Electrodermal activity (EDA) based coupling. For this, multimodal signals are obtained from the publicly available DEAP database (n=32 subjects). The EEG signals are decomposed into θ, α, ß, and bands and EDA signals are decomposed into phasic and tonic components. Then two EEG, three EDA, and two EEG-EDA coupling-based features are extracted and applied to three classifiers namely Random Forest (RF), Linear discriminant analysis, and Adaptive boosting. In addition, SHAP analysis is performed to explain classifiers' performance with respect to features. The result shows that the proposed approach is able to classify valence emotional states. The feature combination of EEG, EDA, and EEG-EDA coupling-based features with an RF classifier performs best with an F1-score of 68.21%. SHAP analysis in frontal electrodes with γ band obtained better discrimination among different valance states. This study underscores the significance of the coupling studies of EEG with EDA in classifying emotion. Therefore, the proposed approach can be extended to emotional state assessment in clinical settings.

Physicochemical characterization of antioxidant film based on ternary blend of chitosan and Tulsi-Ajwain essential oil for preserving walnut.

This study focuses on changes in the physiochemical properties of chitosan film when incorporated with a blend of essential oils of Tulsi and Ajwain. The essential oil blend-loaded films showed a decrement in transparency. Tulsi essential oil decreased the moisture content, swelling capacity, and water solubility. However, adding Ajwain along with Tulsi essential oil led to a significant increase in these properties. Meanwhile, the water vapor transmission rate didn't change significantly due to non-polar constituents in Tulsi essential oil, except when only Ajwain essential oil was present. The mechanical properties showed that the tensile strength of films increased with the addition of Tulsi essential oil (14.95 MPa to 31.27 MPa) but decreased further with increasing Ajwain oil concentration in films (32.13 MPa to 15.89 MPa). On the other hand, an increment in percent elongation at break (8.26 % to 24.02 %) was observed due to the excellent plasticization effect of Ajwain essential oil. Antioxidant activity was observed for the Tulsi essential oil-containing films and increased significantly with adding Ajwain essential oil. Finally, walnuts were packed in the active film. The active film showed better antioxidant activity against the oxidation of oil in walnuts, which the FTIR of the packed product confirmed.

Comparative Study of Ropivacaine and Ropivacaine With Dexmedetomidine in Transversus Abdominis Plane (TAP) Block for Post-operative Analgesia in Patients Undergoing Cesarean Sections.

Background Adequate post-operative analgesia in the obstetric patient is necessary to facilitate breastfeeding and the care of the newborn. Considering the limitations of intravenous analgesic options such as non-steroidal anti-inflammatory drugs (NSAIDs) and opioids, other alternatives have been tried for offering better analgesia with fewer potential side effects. Transversus abdominis plane (TAP) block is one such option that has been tried with various local anesthetic drugs, either alone or in combination with other adjuvants. The addition of dexmedetomidine to bupivacaine in TAP block has been shown to prolong the duration of post-operative analgesia when compared to local anesthetic alone. This study was conducted to determine the efficacy of dexmedetomidine, as an adjuvant to ropivacaine, when administered in TAP block in patients undergoing cesarean section. Methodology The study was a prospective, randomized, parallel assignment, triple-blinded controlled trial. Hundred patients posted for elective lower segment cesarean section, fulfilling the inclusion criteria, were randomly divided into two equal groups, group R and group RD, comprising 50 patients each. Patients in group R were administered bilateral TAP block by landmark technique using ropivacaine alone, whereas patients in group RD were administered TAP block with dexmedetomidine 1 micrograms/kg, in addition to a similar dose of ropivacaine. Mean arterial pressure (MAP), heart rate (HR), visual analog scale (VAS)-R (pain score on VAS scale at rest), VAS-C (pain score on VAS scale on coughing), nausea and vomiting, and Ramsay sedation score were recorded on admission to post-operative care unit (PACU), and at first, fourth, eighth, 12th, 18th, and 24th hours post-operatively. Rescue analgesia was provided with intravenous morphine. Short Assessment of Patient Satisfaction Score (SAPS) was noted on a five-point scale after 24 hours based on patient satisfaction regarding the quality of post-operative analgesia. Results While there was no significant difference between groups R and RD with respect to VAS-C and VAS-R immediately after shifting and at the first, fourth, and eighth hours, a significant difference was observed at the 12th and 18th hours post-operatively. After 24 hours, no significant difference was observed between groups R and RD with respect to VAS-C and VAS-R. While 50% of patients needed rescue analgesia in group R, only 28% of patients needed rescue analgesia in group RD. There was significantly better patient satisfaction measured by the Short Assessment of Patient Satisfaction Score (SAPS) with respect to the quality of analgesia in patients in group RD as compared to those in group R. Conclusions The addition of dexmedetomidine to ropivacaine increased the duration of post-operative analgesia up to 18 hours post-operatively in cases of elective lower segment cesarean section. Also, the quality of post-operative analgesia is better in such patients, as shown by a significant difference in patient satisfaction scores between the two groups.

High dynamic-range and portable magnetometer using ensemble nitrogen-vacancy centers in diamond.

Nitrogen vacancy (NV) centers in diamonds have been explored for a wide range of sensing applications in the last decade due to their unique quantum properties. In this work, we report a compact and portable magnetometer with an ensemble of NV centers, which we call the Quantum MagPI (Quantum Magnetometer with Proportional Integral control). Our fully integrated compact sensor assembly and control electronics fit inside a 10 × 10 × 7 cm3 box and a 30 × 25 × 5 cm3 rack-mountable box, respectively. We achieve a bandwidth normalized sensitivity of ∼10 nT/Hz. Using closed-loop feedback for locking to the resonance frequency, we extend the linear dynamic range to 200 µT (20× improvement compared to the intrinsic dynamic range) without compromising the sensitivity. We report a detailed performance analysis of the magnetometer through measurements of noise spectra, Allan deviation, and tracking of nT-level magnetic fields in real-time. In addition, we demonstrate the utility of such a magnetometer by real-time tracking of the movement of an elevator car and door opening events by measuring the projection of the magnetic field along one of the NV-axes under ambient temperature and humidity conditions.

Highly Sensitive and Selective Fluorescence and Smartphone-Based Sensor for Detection of Rutin Using Boron Nitrogen Co-doped Graphene Quantum Dots.

This research explores the fluorescence properties and photostability of boron nitrogen co-doped graphene quantum dots (BN-GQDs), evaluating their effectiveness as sensors for rutin (RU). BN-GQDs are biocompatible and exhibit notable absorbance and fluorescence characteristics, making them suitable for sensing applications. The study utilized various analytical techniques to investigate the chemical composition, structure, morphology, optical attributes, elemental composition, and particle size of BN-GQDs. Techniques included X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDS), transmission electron microscopy (TEM), scanning electron microscopy (SEM), and atomic force microscopy (AFM). The average particle size of the BN-GQDs was determined to be approximately 3.5 ± 0.3 nm. A clear correlation between the emission intensity ratio and RU concentration was identified across the range of 0.42 to 4.1 µM, featuring an impressively low detection limit (LOD) of 1.23 nM. The application of BN-GQDs as fluorescent probes has facilitated the development of a highly sensitive and selective RU detection method based on Förster resonance energy transfer (FRET) principles. This technique leverages emission at 465 nm. Density Functional Theory (DFT) analyses confirm that FRET is the primary mechanism behind fluorescence quenching, as indicated by the energy levels of the lowest unoccupied molecular orbitals (LUMOs) of BN-GQDs and RU. The method's effectiveness has been validated by measuring RU concentrations in human serum samples, showing a recovery range between 97.8% and 103.31%. Additionally, a smartphone-based detection method utilizing BN-GQDs has been successfully implemented, achieving a detection limit (LOD) of 49 nM.

Arylazo-3,5-diphenylpyrazole Derivatives: Molecular Probes Exhibiting Reversible Light-induced Phase Transitions for Energy Storage and Direct Photolithographic Patterning.

We report azopyrazole photoswitches decorated with variable N-alkyl and alkoxy chains (for hydrophobic interactions) and phenyl substituents on the pyrazoles (enabling π-π stacking), showing efficient bidirectional photoswitching and reversible light-induced phase transition (LIPT). Extensive spectroscopic, microscopic, and diffraction studies and computations confirmed the manifestation of molecular-level interactions and photoisomerization into macroscopic changes leading to the LIPT phenomena. Using differential scanning calorimetric (DSC) studies, the energetics associated with those accompanying processes were estimated. The long half-lives of Z isomers, high energy contents for isomerization and phase transitions, and the stability of phases over an extended temperature range (-60 to 80 °C) make them excellent candidates for energy storage and release applications. Remarkably, the difference in the solubility of the distinct phases in one of the derivatives allowed us to utilize it as a photoresist in photolithography applications on diverse substrates.

Prebiotic diet normalizes aberrant immune and behavioral phenotypes in a mouse model of autism spectrum disorder.

Autism spectrum disorder (ASD) is a cluster of neurodevelopmental disorders characterized by deficits in communication and behavior. Increasing evidence suggests that the microbiota-gut-brain axis and the likely related immune imbalance may play a role in the development of this disorder. Gastrointestinal deficits and gut microbiota dysfunction have been linked to the development or severity of autistic behavior. Therefore, treatments that focus on specific diets may improve gastrointestinal function and aberrant behavior in individuals with ASD. In this study, we investigated whether a diet containing specific prebiotic fibers, namely, 3% galacto-oligosaccharide/fructo-oligosaccharide (GOS/FOS; 9:1), can mitigate the adverse effects of in utero exposure to valproic acid (VPA) in mice. Pregnant BALB/cByJ dams were injected with VPA (600 mg/kg, sc.) or phosphate-buffered saline (PBS) on gestational day 11 (G11). Male offspring were divided into four groups: (1) in utero PBS-exposed with a control diet, (2) in utero PBS-exposed with GOS/FOS diet, (3) in utero VPA-exposed with a control diet, and (4) in utero VPA-exposed with GOS/FOS diet. Dietary intervention started from birth and continued throughout the duration of the experiment. We showed that the prebiotic diet normalized VPA-induced alterations in male offspring, including restoration of key microbial taxa, intestinal permeability, peripheral immune homeostasis, reduction of neuroinflammation in the cerebellum, and impairments in social behavior and cognition in mice. Overall, our research provides valuable insights into the gut-brain axis involvement in ASD development. In addition, dietary interventions might correct the disbalance in gut microbiota and immune responses and, ultimately, might improve detrimental behavioral outcomes in ASD.

Recent Advances in Nanomaterials Based Optical Sensors for the Detection of Melatonin and Serotonin.

In this review paper we discussed the detection of melatonin and serotonin by using various optical methods. Melatonin and serotonin are very necessary body hormones these are also called neuroregulatory hormones secreted by pineal gland in brain by pinealocytes and shape of pineal gland is cone like. Sensitive detection of melatonin and serotonin in pharmacological samples and human serum is crucial for human beings, lots of research publications available in literature for melatonin and serotonin and we overviewed these papers. We have deeply reviewed many research papers where sensitively sensing of melatonin and serotonin occurs, by using of various interfering agents and nanomaterials. This review aims presenting colorimetry, fluorometry and spectrophotometric detection of melatonin (MEL) and serotonin (SER) by using different metal oxides, carbon nanomaterials (nanosheets, nanorods, nanofibers) and many other agents. Nanomaterials typically possess favourable optical, electrical and mechanical characteristics, they provide up new avenues for enhancing the efficacy of sensors. It is crucial to provide an optical sensors platform that is dependable, sensitive and low price. The development of sensors and biosensors to use nanomaterials for neurotransmitters has advanced significantly in recent years. There are currently many developing biomarkers in biological fluids, and bionanomaterial-based biosensor systems, as well as clinical and pharmacological settings, have garnered significant interest. Biomarkers have been found using optical devices in a quick, selective and sensitive manner. Our aim is to compile all the data that already published on MEL, SER sensing and comparison of each method, we mainly focused on principle, observations, sensitivity, selectivity, limit of detection, mechanism behind the reaction, effect of temperature, pH and concentration. In the last of this paper, we discuss some challenges of these methods and future projects.

Validation of a Clinical Tool to Predict Neurological Outcomes in Critically Ill Children-A Prospective Observational Study.

OBJECTIVES: To evaluate the performance of the empiric tool by Gupta et al. in predicting neurological outcomes in children admitted to the pediatric intensive care unit (PICU) and to evaluate the association of biomarkers S100B and NSE with neurological outcomes. METHODS: This prospective observational study was conducted in 163 critically ill children aged 2 mo to 17 y admitted to the PICU from June 2020 to July 2021. The authors used the prediction tool developed by Gupta et al.; the tool was applied at admission and at PICU discharge/death. Samples for NSE and S100B were collected at admission and discharge. The performance of the new tool was assessed through discrimination and calibration. Risk factors for "unfavorable outcomes" (decline in PCPC score by > 1) were evaluated by multivariate analysis. RESULTS: The PICU mortality was 28% (n = 45). When the tool developed by Gupta et al. was used at the time of admission, favorable neurological outcomes were predicted for 69% (112) children. The area under the curve for the new tool at admission was 0.72 and at discharge/death it was 0.99, and the calibration was excellent at both time points. Independent factors associated with unfavorable neurological outcomes were higher PCPC scores and organ failure. As the number of samples processed for NSE and S100B was less, statistical analysis was not attempted. CONCLUSIONS: The new tool by Gupta et al. has good discrimination, calibration, sensitivity, and specificity and can be used as a prediction tool. NSE and S100B are promising biomarkers and need further evaluation.

Polyvinyl alcohol-derived-carbon quantum dots based fluorometric "On-Off" probe for moxifloxacin detection in milk and egg samples.

Unconditional use of antibiotics triggered the process of bacterial resistance and causes major health problems. Nowadays, antibiotics majorly used in animals not only for infection treatment but also as mass promotor. The excess amount of antibiotics residue in animal derived foods which accelerate antibiotic resistance (ABR). So, here, a simple and quick carbon quantum dots(CQDs) based fluorometric "On-Off" probe was developed for detection of moxifloxacin (MOXI) in milk and egg samples. The CQDs emits blue emission and are uniformly distributed with average particle size 5.9 ± 0.22 nm. With MOXI, fluorescence intensity of CQDs at 372 nm decreased due to inner filter effect (IFE) and a new peak appeared at 508 nm correspondence to MOXI. The probe shows linear response with MOXI concentration varies as 0.025 µM - 15.0 µM with lower detection limit (LOD) of 6.34 nM. The real sample applicability test proved that the sensors have excellent efficacy for food applications.

Current Landscape of Therapeutics for the Management of Hypertension - A Review.

Hypertension is a critical health problem. It is also the primary reason for coronary heart disease, stroke, and renal vascular disease. The use of herbal drugs in the management of any disease is increasing. They are considered the best immune booster to fight against several types of diseases. To date, the demand for herbal drugs has been increasing because of their excellent properties. This review highlights antihypertensive drugs, polyphenols, and synbiotics for managing hypertension. Evidence is mounting in favour of more aggressive blood pressure control with reduced adverse effects, especially for specific patient populations. This review aimed to present contemporary viewpoints and novel treatment options, including cutting-edge technological applications and emerging interventional and pharmaceutical therapies, as well as key concerns arising from several years of research and epidemiological observations related to the management of hypertension.

Interplay of host and viral factors in inflammatory pathway mediated cytokine storm during RNA virus infection.

RNA viruses always have been a serious concern for human health by causing several outbreaks, often pandemics. The excessive mortality and deaths associated with the outbreaks caused by these viruses were due to the excessive induction of pro-inflammatory cytokines leading to cytokine storm. Cytokines are important for cell-to-cell communication to maintain cell homeostasis. Disturbances of this homeostasis can lead to intricate chain reactions resulting in a massive release of cytokines. This could lead to a severe self-reinforcement of several feedback processes, which could eventually cause systemic harm, multiple organ failure, or death. Multiple inflammation-associated pathways were involved in the cytokine production and its regulation. Different RNA viruses induce these pathways through the interplay with their viral factors and host proteins and miRNAs regulating these pathways. This review will discuss the interplay of host proteins and miRNAs that can play an important role in the regulation of cytokine storm and the possible therapeutic potential of these molecules for the treatment and the challenges associated with the clinical translation.

Bistable Aryl Azopyrazolium Ionic Photoswitches in Water.

We report a new class of arylazopyrazolium-based ionic photoswitches (AAPIPs). These AAPIPs with different counter ions have been accessed through a modular synthetic approach in high yields. More importantly, the AAPIPs exhibit excellent reversible photoswitching and exceptional thermal stability in water. The effects of solvents, counter ions, substitutions, concentration, pH, and glutathione (GSH) have been evaluated using spectroscopic investigations. The results revealed that the bistability of studied AAPIPs is robust and near quantitative. The thermal half-life of Z isomers is extremely high in water (up to years), and it can be lowered electronically by the electron-withdrawing groups or highly basic pH.

Whey-based diet containing medium chain triglycerides modulates the gut microbiota and protects the intestinal mucosa from chemotherapy while maintaining therapy efficacy.

Cytotoxicity (i.e. cell death) is the core mechanism by which chemotherapy induces its anti-cancer effects. Unfortunately, this same mechanism underpins the collateral damage it causes to healthy tissues. The gastrointestinal tract is highly susceptible to chemotherapy's cytotoxicity, resulting in ulcerative lesions (termed gastrointestinal mucositis, GI-M) that impair the functional capacity of the gut leading to diarrhea, anorexia, malnutrition and weight loss, which negatively impact physical/psychological wellbeing and treatment adherence. Preventing these side effects has proven challenging given the overlapping mechanisms that dictate chemotherapy efficacy and toxicity. Here, we report on a novel dietary intervention that, due to its localized gastrointestinal effects, is able to protect the intestinal mucosal from unwanted toxicity without impairing the anti-tumor effects of chemotherapy. The test diet (containing extensively hydrolyzed whey protein and medium chain triglycerides (MCTs)), was investigated in both tumor-naïve and tumor-bearing models to evaluate its effect on GI-M and chemo-efficacy, respectively. In both models, methotrexate was used as the representative chemotherapeutic agent and the diet was provided ad libitum for 14 days prior to treatment. GI-M was measured using the validated biomarker plasma citrulline, and chemo-efficacy defined by tumor burden (cm3/g body weight). The test diet significantly attenuated GI-M (P = 0.03), with associated reductions in diarrhea (P < 0.0001), weight loss (P < 0.05), daily activity (P < 0.02) and maintenance of body composition (P < 0.02). Moreover, the test diet showed significant impact on gut microbiota by increasing diversity and resilience, whilst also altering microbial composition and function (indicated by cecal short and brained chain fatty acids). The test diet did not impair the efficacy of methotrexate against mammary adenocarcinoma (tumor) cells. In line with the first model, the test diet minimized intestinal injury (P = 0.001) and diarrhea (P < 0.0001). These data support translational initiatives to determine the clinical feasibility, utility and efficacy of this diet to improve chemotherapy treatment outcomes.

Impulsivity Classification Using EEG Power and Explainable Machine Learning.

Impulsivity is a multidimensional construct often associated with unfavorable outcomes. Previous studies have implicated several electroencephalography (EEG) indices to impulsiveness, but results are heterogeneous and inconsistent. Using a data-driven approach, we identified EEG power features for the prediction of self-reported impulsiveness. To this end, EEG signals of 56 individuals (18 low impulsive, 20 intermediate impulsive, 18 high impulsive) were recorded during a risk-taking task. Extracted EEG power features from 62 electrodes were fed into various machine learning classifiers to identify the most relevant band. Robustness of the classifier was varied by stratified [Formula: see text]-fold cross validation. Alpha and beta band power showed best performance in the classification of impulsiveness (accuracy = 95.18% and 95.11%, respectively) using a random forest classifier. Subsequently, a sequential bidirectional feature selection algorithm was used to estimate the most relevant electrode sites. Results show that as little as 10 electrodes are sufficient to reliably classify impulsiveness using alpha band power ([Formula: see text]-measure = 94.50%). Finally, the Shapley Additive exPlanations (SHAP) analysis approach was employed to reveal the individual EEG features that contributed most to the model's output. Results indicate that frontal as well as posterior midline alpha power seems to be of most importance for the classification of impulsiveness.

Machine learning-driven blood transcriptome-based discovery of SARS-CoV-2 specific severity biomarkers.

The Coronavirus disease 2019 (COVID-19) pandemic, caused by rapidly evolving variants of severe acute respiratory syndrome coronavirus (SARS-CoV-2), continues to be a global health threat. SARS-CoV-2 infection symptoms often intersect with other nonsevere respiratory infections, making early diagnosis challenging. There is an urgent need for early diagnostic and prognostic biomarkers to predict severity and reduce mortality when a sudden outbreak occurs. This study implemented a novel approach of integrating bioinformatics and machine learning algorithms over publicly available clinical COVID-19 transcriptome data sets. The robust 7-gene biomarker identified through this analysis can not only discriminate SARS-CoV-2 associated acute respiratory illness (ARI) from other types of ARIs but also can discriminate severe COVID-19 patients from nonsevere COVID-19 patients. Validation of the 7-gene biomarker in an independent blood transcriptome data set of longitudinal analysis of COVID-19 patients across various stages of the disease showed that the dysregulation of the identified biomarkers during severe disease is restored during recovery, showing their prognostic potential. The blood biomarkers identified in this study can serve as potential diagnostic candidates and help reduce COVID-19-associated mortality.